This got me thinking about big data (an important buzz word recently), healthcare in general, and the role of Health Language and medical terminology management in DIY healthcare interoperability.

What is big data? It’s the huge volume of structured and unstructured data, from a variety of sources, that are generated and aggregated continuously and with accelerating velocity. Big data in healthcare is the mountain of information contained in millions of healthcare insurance claims submitted each month, plus the data in the charts and electronic health records in doctors’ offices, plus the data in labs, hospitals, clinics, and patients’ own charts and EHRs.

The implications of big data and its effective use for evidence-based medicine are well-known, but less-discussed is the impact of big data on the potential for expansion of the Do It Yourself (DIY) healthcare market.

DIY home healthcare has been around since the invention of the fever thermometer and the bathroom scale and the home pregnancy test many decades ago, but electronic methods of gathering, assessing, and distributing data are making sophisticated DIY healthcare testing equipment and methods commonplace—the consumer can buy strep throat test kits on Amazon, for example. Armed with better information about her kids’ symptoms, a mother can make better choices about bringing the kids to an urgent care clinic, to her primary physician’s office, or to the hospital emergency room—and may be able to avoid an incorrect, costly, and time-consuming healthcare choice.

In an online world, consumers will increasingly demand access to empowering DIY healthcare solutions and information, and will increasingly produce their own healthcare data. If I perform a cholesterol test at home, rather than with a $200 visit to my primary care physician’s office, how can I add that DIY information to my own EHR, and make it a part of my own record?

This is where Health Language (HLI) can play a key role. As in so many areas of healthcare delivery and management, standardization of information is key. Healthcare information in a silo is useless; with effective interoperability information from all parts of a patient’s healthcare landscape—primary care office, lab, hospital, clinic, pharmacy, and DIY at home—can be aggregated for access by the patient and her doctors anytime and anywhere.

DIY health is about collecting data in a cost-effective and convenient way—Health Language is about standardizing the data and making it usable across the healthcare landscape:

With HLI terminology management, unstructured DIY data can be normalized to conform with emerging ICD-10, Meaningful Use, and interoperability requirements.

HLI provides specialized content such as Provider Friendly Terminology (PFT) and Consumer Friendly Terminology (CFT), to help make clinical terms accessible to the lay person.

With standardized information, communication between the clinical EHR and the DIY patient is two-way: structured patient data can be uploaded to the EHR, and EHR data can become more easily accessible to the empowered patient for informed decision-making.

In this way DIY healthcare data becomes a part of big data, and can be stored in the data warehouse for distribution and use, in a way that is invisible to the consumer. The empowered patient knows only that the data is current, accurate, and available—and can make informed, cost-effective decisions about his or her own healthcare.